Overview

Welcome! This website contains a collection of graphs composed in using ggplot2 (and friends!).

Install ggplot2 using the code below:

Code

install.packages("ggplot2")
library(ggplot2)

Or install ggplot2 as part of the tidyverse:

Code

install.packages("tidyverse")
library(tidyverse)

The Data

To improve reproducibility, the majority of the graphs are built using the palmerpenguins::penguins data.

…so…many…PENGUINS!

Artwork by @allison_horst

Code

install.packages("palmerpenguins")
library(palmerpenguins)

Some of the graphs use datasets from the fivethirtyeight package.

Code

install.packages("fivethirtyeight")
library(fivethirtyeight)

Expand to view the data in the fivethirtyeight package

To view a table of available datasets in the fivethirtyeight package, view the Data Frame Name and Article Title columns in the datasets_master table:

A few of the graphs are built using the ggplot2movies::movies data.

Code

install.packages("ggplot2movies")
library(ggplot2movies)

The Graphs (code style & structure)

The gallery follows a Rule of Least Power Principle, in the sense that “a language with a straightforward syntax may be easier to analyze than an otherwise equivalent one with more complex structure.”

In other words, assuming the reader has some understanding of R and the tidyverse, the code for each graph is meant to be read and understood without having to run it.

Each graph has the same four sections and structure: Packages, Data, Code, and Graph

Expand to view the graph code structure

Packages

PACKAGES:

Install packages.

Code

library(ggplot2)

Data

DATA:

Description of data

Code

df <- tibble::tibble(X = sample(x = 1:100, 10, FALSE),
                     Y = rlnorm(10, 1, 3))

Code

CODE:

Code for creating graph

Code

# labels
labs_graph <- ggplot2::labs(title = "Title", 
                            subtitle = "subtitle", 
                            x = "X", y = "Y")
# layers
ggp2_graph <- ggplot2::ggplot(data = df, 
    mapping = aes(x = X, y = Y)) + 
    ggplot2::geom_blank()
# graph
ggp2_graph + 
    labs_graph

Graph

GRAPH:

All objects have the following naming conventions:

• Graph labels have the labs_ prefix

• Graph layers have a ggp2_ prefix

Code Style:

I’ve attempted to balance brevity and clarity, but with the assumption that its best to err on the latter. I’ve also followed the general principle that if a graph can be easily built using one of ggplot2 ’s geom_* functions, that method is shown first.

If the graph can’t be built with ggplot2’s geoms and requires additional packages/geoms/functions, instructions for installing the development version for these packages has been provided.

Extensions:

Below are the graphs requiring additional packages/extensions:

• Waffle charts

  • ggwaffle package

    Code

    # Waffle Charts
    devtools::install_github("liamgilbey/ggwaffle")
    library(ggwaffle)

• Pie Charts

  • ggpubr package

    Code

    # Pie Charts 
    devtools::install_github("kassambara/ggpubr")
    library(ggpubr)

• Mosaic Plots

  • ggmosaic package

    Code

    # Mosaic Charts 
    devtools::install_github("haleyjeppson/ggmosaic")
    library(ggmosaic)

• Treemaps

  • treemapify package

    Code

    # Treemaps
    devtools::install_github("wilkox/treemapify")
    library(treemapify)

• Bee-swarm Plots

  • ggbeeswarm package

    Code

    # Bee-swarm Plots
    devtools::install_github("eclarke/ggbeeswarm")
    library(ggbeeswarm)

• Ridgeline Plots

  • ggridges package

    Code

    # Ridgeline plots 
    devtools::install_github("wilkelab/ggridges")
    library(ggridges)

• Rain-cloud plots

  • raincloudplots and ggdist packages

    Code

    # Rain-cloud plots 
    remotes::install_github('jorvlan/raincloudplots')
    remotes::install_github('mjskay/ggdist')
    library(raincloudplots)
    library(ggdist)

• Alluvial charts

  • ggalluvial package

    Code

    # Alluvial charts
    devtools::install_github("corybrunson/ggalluvial")
    library(ggalluvial)

• Bump charts

  • ggbump package

    Code

    # Bump charts
    devtools::install_github("davidsjoberg/ggbump")
    library(ggbump)

• Parallel Sets

  • ggforce package

    Code

    # Bump charts
    devtools::install_github("thomasp85/ggforce")
    library(ggforce)

Graph Categories

Graphs have been categorized into the following types:

• Univariate graphs
  
• Amounts
• Proportions
  
• Comparing Distributions
  
• Relationships

Some graphs would justifiably belong in more than one category, and wherever this is the cases, I’ve tried to include other uses in the notes.